Construction of an economical xylose-utilizing Saccharomyces cerevisiae and its ethanol fermentation.

Traditional industrial Saccharomyces cerevisiae could not metabolize xylose due to the lack of a specific enzyme system for the reaction from xylose to xylulose. This study aims to metabolically remould industrial S. cerevisiae for the purpose of utilizing both glucose and xylose with high efficiency. Heterologous gene xylA from Piromyces and homologous genes related to xylose utilization were selected to construct expression cassettes and integrated into genome. The engineered strain was domesticated with industrial material under optimizing conditions subsequently to further improve xylose utilization rates. The resulting S. cerevisiae strain ABX0928-0630 exhibits a rapid growth rate and possesses near 100% xylose utilization efficiency to produce ethanol with industrial material. Pilot-scale fermentation indicated the predominant feature of ABX0928-0630 for industrial application, with ethanol yield of 0.48 g/g sugars after 48 hours and volumetric xylose consumption rate of 0.87 g/l/h during the first 24 hours. Transcriptome analysis during the modification and domestication process revealed a significant increase in the expression level of pathways associated with sugar metabolism and sugar sensing. Meanwhile, genes related to glycerol lipid metabolism exhibited a pattern of initial increase followed by a subsequent decrease, providing a valuable reference for the construction of efficient xylose-fermenting strains.

Gene-by-environment interactions influence the fitness cost of gene copy-number variation in yeast.

Variation in gene copy number can alter gene expression and influence downstream phenotypes; thus copy-number variation provides a route for rapid evolution if the benefits outweigh the cost. We recently showed that genetic background significantly influences how yeast cells respond to gene overexpression, revealing that the fitness costs of copy-number variation can vary substantially with genetic background in a common-garden environment. But the interplay between copy-number variation tolerance and environment remains unexplored on a genomic scale. Here, we measured the tolerance to gene overexpression in four genetically distinct Saccharomyces cerevisiae strains grown under sodium chloride stress. Overexpressed genes that are commonly deleterious during sodium chloride stress recapitulated those commonly deleterious under standard conditions. However, sodium chloride stress uncovered novel differences in strain responses to gene overexpression. West African strain NCYC3290 and North American oak isolate YPS128 are more sensitive to sodium chloride stress than vineyard BC187 and laboratory strain BY4743. Consistently, NCYC3290 and YPS128 showed the greatest sensitivities to overexpression of specific genes. Although most genes were deleterious, hundreds were beneficial when overexpressed-remarkably, most of these effects were strain specific. Few beneficial genes were shared between the sodium chloride-sensitive isolates, implicating mechanistic differences behind their sodium chloride sensitivity. Transcriptomic analysis suggested underlying vulnerabilities and tolerances across strains, and pointed to natural copy-number variation of a sodium export pump that likely contributes to strain-specific responses to overexpression of other genes. Our results reveal extensive strain-by-environment interactions in the response to gene copy-number variation, raising important implications for the accessibility of copy-number variation-dependent evolutionary routes under times of stress.

Elevated energy costs of biomass production in mitochondrial respiration-deficient Saccharomyces cerevisia.

Microbial growth requires energy for maintaining the existing cells and producing components for the new ones. Microbes therefore invest a considerable amount of their resources into proteins needed for energy harvesting. Growth in different environments is associated with different energy demands for growth of yeast Saccharomyces cerevisiae, although the cross-condition differences remain poorly characterized. Furthermore, a direct comparison of the energy costs for the biosynthesis of the new biomass across conditions is not feasible experimentally; computational models, on the contrary, allow comparing the optimal metabolic strategies and quantify the respective costs of energy and nutrients. Thus in this study, we used a resource allocation model of S. cerevisiae to compare the optimal metabolic strategies between different conditions. We found that S. cerevisiae with respiratory-impaired mitochondria required additional energetic investments for growth, while growth on amino acid-rich media was not affected. Amino acid supplementation in anaerobic conditions also was predicted to rescue the growth reduction in mitochondrial respiratory shuttle-deficient mutants of S. cerevisiae. Collectively, these results point to elevated costs of resolving the redox imbalance caused by de novo biosynthesis of amino acids in mitochondria. To sum up, our study provides an example of how resource allocation modeling can be used to address and suggest explanations to open questions in microbial physiology.

Yeast has evolved to minimize protein resource cost for synthesizing amino acids.

Proteins, as essential biomolecules, account for a large fraction of cell mass, and thus the synthesis of the complete set of proteins (i.e., the proteome) represents a substantial part of the cellular resource budget. Therefore, cells might be under selective pressures to optimize the resource costs for protein synthesis, particularly the biosynthesis of the 20 proteinogenic amino acids. Previous studies showed that less energetically costly amino acids are more abundant in the proteomes of bacteria that survive under energy-limited conditions, but the energy cost of synthesizing amino acids was reported to be weakly associated with the amino acid usage in Saccharomyces cerevisiae Here we present a modeling framework to estimate the protein cost of synthesizing each amino acid (i.e., the protein mass required for supporting one unit of amino acid biosynthetic flux) and the glucose cost (i.e., the glucose consumed per amino acid synthesized). We show that the logarithms of the relative abundances of amino acids in S. cerevisiae's proteome correlate well with the protein costs of synthesizing amino acids (Pearson's r = -0.89), which is better than that with the glucose costs (Pearson's r = -0.5). Therefore, we demonstrate that S. cerevisiae tends to minimize protein resource, rather than glucose or energy, for synthesizing amino acids.

Assessment of Cre-lox and CRISPR-Cas9 as tools for recycling of multiple-integrated selection markers in Saccharomyces cerevisiae.

We evaluated the Cre-lox and CRISPR-Cas9 systems as marker-recycling tools in Saccharomyces cerevisiae recombinants containing multiple-integrated expression cassettes. As an initial trial, we constructed rDNA-nontranscribed spacer- or Ty4-based multiple integration vectors containing the URA3 marker flanked by the loxP sequence. Integrants harboring multiple copies of tHMG1 and NNV-CP expression cassettes were obtained and subsequently transformed with the Cre plasmid. However, the simultaneous pop-out of the expression cassettes along with the URA3 marker hampered the use of Cre-lox as a marker-recycling tool in multiple integrants. As an alternative, we constructed a set of CRISPR-Cas9-gRNA vectors containing gRNA targeted to auxotrophic marker genes. Transformation of multiple integrants of tHMG1 and NNV-CP cassettes by the Cas9-gRNA vector in the presence of the URA3 (stop) donor DNA fragments generated the Ura- transformants retaining multiple copies of the expression cassettes. CRISPR-Cas9-based inactivation led to the recycling of the other markers, HIS3, LEU2, and TRP1, without loss of expression cassettes in the recombinants containing multiple copies of tHMG1, NNV-CP, and SfBGL1 cassettes, respectively. Reuse of the same selection marker in marker-inactivated S. cerevisiae was validated by multiple integrations of the TrEGL2 cassette into the S. cerevisiae strain expressing SfBGL1. These results demonstrate that introducing stop codons into selection marker genes using the CRISPR-Cas9 system with donor DNA fragments is an efficient strategy for markerrecycling in multiple integrants. In particular, the continual reuse of auxotrophic markers would facilitate the construction of a yeast cell factory containing multiple copies of expression cassettes without antibiotic resistance genes.

A prion accelerates proliferation at the expense of lifespan.

In fluctuating environments, switching between different growth strategies, such as those affecting cell size and proliferation, can be advantageous to an organism. Trade-offs arise, however. Mechanisms that aberrantly increase cell size or proliferation-such as mutations or chemicals that interfere with growth regulatory pathways-can also shorten lifespan. Here we report a natural example of how the interplay between growth and lifespan can be epigenetically controlled. We find that a highly conserved RNA-modifying enzyme, the pseudouridine synthase Pus4/TruB, can act as a prion, endowing yeast with greater proliferation rates at the cost of a shortened lifespan. Cells harboring the prion grow larger and exhibit altered protein synthesis. This epigenetic state, [BIG+] (better in growth), allows cells to heritably yet reversibly alter their translational program, leading to the differential synthesis of dozens of proteins, including many that regulate proliferation and aging. Our data reveal a new role for prion-based control of an RNA-modifying enzyme in driving heritable epigenetic states that transform cell growth and survival.

Cells make different proteins to perform different tasks. Each protein is a long chain of building blocks called amino acids that must fold into a particular shape before it can be useful. Some proteins can fold in more than one way, a normal form and a 'prion' form. Prions are unusual in that they can force normally folded proteins with the same amino acid sequence as them to refold into new prions. This means that a single prion can make many more that are inherited when cells divide. Some prions can cause disease, but others may be beneficial. Pus4 is a yeast protein that is typically involved in modifying ribonucleic acids, molecules that help translate genetic information into new proteins. Sometimes Pus4 can adopt a beneficial prion conformation called [BIG⁺]. When yeast cells have access to plenty of nutrients, [BIG⁺] helps them grow faster and larger, but this comes at the cost of a shorter lifespan. Garcia, Campbell et al. combined computational modeling and experiments in baker's yeast (Saccharomyces cerevisiae) to investigate the role of [BIG⁺]. They found that the prion accelerated protein production, leading to both faster growth and a shorter lifespan in these cells, even without any changes in gene sequence. Garcia, Campbell et al.'s findings explain the beneficial activity of prion proteins in baker's yeast cells. The results also describe how cells balance a tradeoff between growth and lifespan without any changes in the genome. This helps to highlight that genetics do not always explain the behaviors of cells, and further methods are needed to better understand cell biology.

Development of a method for heat shock stress assessment in yeast based on transcription of specific genes.

All living cells, including yeast cells, are challenged by different types of stresses in their environments and must cope with challenges such as heat, chemical stress, or oxidative damage. By reversibly adjusting the physiology while maintaining structural and genetic integrity, cells can achieve a competitive advantage and adapt environmental fluctuations. The yeast Saccharomyces cerevisiae has been extensively used as a model for study of stress responses due to the strong conservation of many essential cellular processes between yeast and human cells. We focused here on developing a tool to detect and quantify early responses using specific transcriptional responses. We analyzed the published transcriptional data on S. cerevisiae DBY strain responses to 10 different stresses in different time points. The principal component analysis (PCA) and the Pearson analysis were used to assess the stress response genes that are highly expressed in each individual stress condition. Except for these stress response genes, we also identified the reference genes in each stress condition, which would not be induced under stress condition and show stable transcriptional expression over time. We then tested our candidates experimentally in the CEN.PK strain. After data analysis, we identified two stress response genes (UBI4 and RRP) and two reference genes (MEX67 and SSY1) under heat shock (HS) condition. These genes were further verified by real-time PCR at mild (42°C), severe (46°C), to lethal temperature (50°C), respectively.

A comprehensive mechanism for 5-carboxylcytosine-induced transcriptional pausing revealed by Markov state models.

RNA polymerase II (Pol II) surveils the genome, pausing as it encounters DNA lesions and base modifications and initiating signals for DNA repair among other important regulatory events. Recent work suggests that Pol II pauses at 5-carboxycytosine (5caC), an epigenetic modification of cytosine, because of a specific hydrogen bond between the carboxyl group of 5caC and a specific residue in fork loop 3 of Pol II. This hydrogen bond compromises productive NTP binding and slows down elongation. Apart from this specific interaction, the carboxyl group of 5caC can potentially interact with numerous charged residues in the cleft of Pol II. However, it is not clear how other interactions between Pol II and 5caC contribute to pausing. In this study, we use Markov state models (a type of kinetic network models) built from extensive molecular dynamics simulations to comprehensively study the impact of 5caC on Pol II translocation. We describe two translocation intermediates with specific interactions that prevent the template base from loading into the Pol II active site. In addition to the previously observed state with 5caC constrained by fork loop 3, we discovered a new intermediate state with a hydrogen bond between 5caC and fork loop 2. Surprisingly, we find that 5caC may curb translocation by suppressing kinking of the helix bordering the active site (the bridge helix) because its high flexibility is critical to translocation. Our work provides new insights into how epigenetic modifications of genomic DNA can modulate Pol II translocation, inducing pauses in transcription.

Multiplexing mutation rate assessment: determining pathogenicity of Msh2 variants in Saccharomyces cerevisiae.

Despite the fundamental importance of mutation rate as a driving force in evolution and disease risk, common methods to assay mutation rate are time-consuming and tedious. Established methods such as fluctuation tests and mutation accumulation experiments are low-throughput and often require significant optimization to ensure accuracy. We established a new method to determine the mutation rate of many strains simultaneously by tracking mutation events in a chemostat continuous culture device and applying deep sequencing to link mutations to alleles of a DNA-repair gene. We applied this method to assay the mutation rate of hundreds of Saccharomyces cerevisiae strains carrying mutations in the gene encoding Msh2, a DNA repair enzyme in the mismatch repair pathway. Loss-of-function mutations in MSH2 are associated with hereditary nonpolyposis colorectal cancer, an inherited disorder that increases risk for many different cancers. However, the vast majority of MSH2 variants found in human populations have insufficient evidence to be classified as either pathogenic or benign. We first benchmarked our method against Luria-Delbrück fluctuation tests using a collection of published MSH2 missense variants. Our pooled screen successfully identified previously characterized nonfunctional alleles as high mutators. We then created an additional 185 human missense variants in the yeast ortholog, including both characterized and uncharacterized alleles curated from ClinVar and other clinical testing data. In a set of alleles of known pathogenicity, our assay recapitulated ClinVar's classification; we then estimated pathogenicity for 157 variants classified as uncertain or conflicting reports of significance. This method is capable of studying the mutation rate of many microbial species and can be applied to problems ranging from the generation of high-fidelity polymerases to measuring the frequency of antibiotic resistance emergence.

Quantitative assessment of the determinant structural differences between redox-active and inactive glutaredoxins.

Class I glutaredoxins are enzymatically active, glutathione-dependent oxidoreductases, whilst class II glutaredoxins are typically enzymatically inactive, Fe-S cluster-binding proteins. Enzymatically active glutaredoxins harbor both a glutathione-scaffold site for reacting with glutathionylated disulfide substrates and a glutathione-activator site for reacting with reduced glutathione. Here, using yeast ScGrx7 as a model protein, we comprehensively identified and characterized key residues from four distinct protein regions, as well as the covalently bound glutathione moiety, and quantified their contribution to both interaction sites. Additionally, we developed a redox-sensitive GFP2-based assay, which allowed the real-time assessment of glutaredoxin structure-function relationships inside living cells. Finally, we employed this assay to rapidly screen multiple glutaredoxin mutants, ultimately enabling us to convert enzymatically active and inactive glutaredoxins into each other. In summary, we have gained a comprehensive understanding of the mechanistic underpinnings of glutaredoxin catalysis and have elucidated the determinant structural differences between the two main classes of glutaredoxins.

Biocompatibility assessment of Fe3O4 nanoparticles using Saccharomyces cerevisiae as a model organism.

Using Saccharomyces cerevisiae as an experimental model, the potential toxicological effects of Fe3O4 nanoparticles (Fe3O4-NPs) were investigated following exposure to 0-600 mg/L for 24 h. Results revealed that cell proliferation was significantly inhibited by Fe3O4-NPs with an IC50 value of 326.66 mg/L. Mortality showed a concentration-dependent increase, and the highest concentration in this study (600 mg/L) resulted in 22.30% mortality. In addition, Effects on proliferation and mortality were accounted for Fe3O4-NPs rather than iron ion released from Fe3O4-NPs. Scanning and transmission electron microscope observation showed that Fe3O4-NPs extensively attached on the cell surfaces, causing cells to deform and shrink. Moreover, Fe3O4-NPs could be internalized in S. cerevisiae cells via endocytosis and then be distributed in cytoplasm and vesicles. The data of uptake kinetics demonstrated that the maximal accumulation (4.898 mg/g) was reached at 15 h. Besides, percentage of late apoptosis/necrosis was observably increased (p < 0.01) at 600 mg/L (15.80%), and the expression levels of apoptosis-related genes (SOD, Yca1 and Nuc1) were dramatically increased following exposure to Fe3O4-NPs for 24 h. As expected, mitochondrial transmembrane potential was significantly decreased (p < 0.01) at 50-600 mg/L, and biomarkers of oxidative stress (ROS, CAT and SOD) were also markedly changed following exposure. Altogether, the combined results so far indicated Fe3O4-NPs could induce S. cerevisiae cell apoptosis that mediated by mitochondrial impairment and oxidative stress.

DNMHMM: An approach to identify the differential nucleosome regions in multiple cell types based on a Hidden Markov Model.

Nucleosome occupancy changes across cell types and environmental conditions and such changes often have profound influence in transcription. It's of importance to identify the differential nucleosome regions (DNRs) where the nucleosome occupancy level differs across cell types. Here we developed DNMHMM, a Hidden Markov Model (HMM) based algorithm, to detect the DNRs with nucleosomal DNA sequenced dataset. The performance evaluation indicates that DNMHMM is advisable for multi-cell type comparison. Upon testing this model in yeast mutants, where the modifiable histone residues were mutated into alanine, we found that DNA sequences of the dynamic nucleosomes lack 10-11 bp periodicities and harbor binding motifs of the nucleosome remodelling complex. Moreover, the highly expressed genes have more dynamic nucleosomes at promoters. We further compared nucleosome occupancy between resting and activated human CD4+ T cells with this model. It was revealed that during the activation of CD4+ T cells, dynamic nucleosomes are enriched at regulatory sites, hence, up to some extent can affect the gene expression level. Taken together, DNMHMM offers the possibility to access precise nucleosome dynamics among multiple cell types and also can describe the closer association between nucleosome and transcription.

Quantitative assessment of changes in cell growth, size and morphology during telomere-initiated cellular senescence in Saccharomyces cerevisiae.

Telomerase-deficient cells of the budding yeast S. cerevisiae experience progressive telomere shortening and undergo senescence in a manner similar to that seen in cultured human fibroblasts. The cells exhibit a DNA damage checkpoint-like stress response, undergo changes in size and morphology, and eventually stop dividing. In this study, a new assay is described that allowed quantitation of senescence in telomerase-deficient est2 cells with applied statistics. Use of the new technique revealed that senescence was strongly accelerated in est2 mutants that had homologous recombination genes RAD51, RAD52 or RAD54 co-inactivated, but was only modestly affected when RAD55, RAD57 or RAD59 were knocked out. Additionally, a new approach for calculating population doublings indicated that loss of growth capacity occurred after approximately 64 generations in est2 cells but only 42 generations in est2 rad52 cells. Phase contrast microscopy experiments demonstrated that senescing est2 cells became enlarged in a time-dependent manner, ultimately exhibiting a 60% increase in cell size. Progressive alterations in physical properties were also observed, including striking changes in light scattering characteristics and cellular sedimentation rates. The results described herein will facilitate future studies of genetic and environmental factors that affect telomere shortening-associated cell senescence rates using the yeast model system.

The fitness landscape of the codon space across environments.

Fitness landscapes map the relationship between genotypes and fitness. However, most fitness landscape studies ignore the genetic architecture imposed by the codon table and thereby neglect the potential role of synonymous mutations. To quantify the fitness effects of synonymous mutations and their potential impact on adaptation on a fitness landscape, we use a new software based on Bayesian Monte Carlo Markov Chain methods and re-estimate selection coefficients of all possible codon mutations across 9 amino acid positions in Saccharomyces cerevisiae Hsp90 across 6 environments. We quantify the distribution of fitness effects of synonymous mutations and show that it is dominated by many mutations of small or no effect and few mutations of larger effect. We then compare the shape of the codon fitness landscape across amino acid positions and environments, and quantify how the consideration of synonymous fitness effects changes the evolutionary dynamics on these fitness landscapes. Together these results highlight a possible role of synonymous mutations in adaptation and indicate the potential mis-inference when they are neglected in fitness landscape studies.

A low cost PS based microfluidic platform to investigate cell cycle towards developing a therapeutic strategy for cancer.

Inhibition of DNA damage response pathway in combination with DNA alkylating agents may enhance the selective killing of cancer cells leading to better therapeutic effects. MDM2 binding protein (MTBP) in human has a role in G1 phase (interphase of cell cycle) and its overexpression leads to breast and ovarian cancers. Sld7 is an uncharacterized protein in budding yeast and a potential functional homologue of MTBP. To investigate the role of Sld7 as a therapeutic target, the behavior of the wild-type cells and sld7∆ mutants were monitored in 0.5 nL microbioreactors. The brightfield microscopy images were used to analyze the change in the cell size and to determine the durations of G1 and S/G2/M phases of wild type cells and mutants. With the administration of the alkylating agent, the cell size decreased and the duration of cell cycle increased. The replacement of the medium with the fresh one enabled the cells to repair their DNA. The application of calorie restriction together with DNA alkylating agent to mutant cells resulted in smaller cell size and longer G1 phase compared to those in control environment. For therapeutic purposes, the potential of MTBP in humans or Sld7 in yeast as a drug target deserves further exploration. The fabrication simplicity, robustness and low-cost of this microfluidic bioreactor made of polystyrene allowed us to perform yeast culturing experiments and show a potential for further cell culturing studies. The device can successfully be used for therapeutic applications including the discovery of new anti-microbial, anti-inflammatory, anti-cancer drugs.

A multi-column plate adapter provides an economical and versatile high-throughput protein purification system.

Protein purification is essential in the study of protein structure and function, and the development of novel therapeutics. Many studies require purifying multiple proteins at once, increasing the demand for improved purification methods. We hypothesized that multiple chromatography columns could be interfaced with a multi-well collection plate for rapid and convenient protein purification without the need of expensive instrumentation. As such, we developed a multi-column plate adapter (MCPA), which provides an economical yet versatile and time efficient, high-throughput protein purification system. The MCPA system simultaneously purified milligrams of different proteins under gravity or under vacuum for faster purification. The MCPA handles up to twenty-four 12 mL columns and multiple MCPA's in sequence allow milligram-scale purification of 96 different samples with relative ease. We also used the MCPA system for large scale affinity purification of four proteins, providing sufficient yields and purity for protein crystallization and biophysical characterization. The MCPA system is ideal for optimizing resin type and volume or any other purification parameter by customizing individual columns during the same purification. The high-throughput and versatile nature of this system should prove to be useful in obtaining adequate amounts of protein for subsequent analyses in any laboratory setting.

Asynchrony of Base-Pair Breaking and Nucleotide Releasing of Helicases in DNA Unwinding.

Helicases harness the energy of nucleotide triphosphate hydrolysis to unwind double-stranded DNA (dsDNA) in discrete steps. In spite of intensive studies, the mechanism of stepping is still poorly understood. Here, we applied single-molecule fluorescent resonant energy transfer to characterize the stepping of two nonring helicases, Escherichia coli RecQ ( E. coli RecQ) and Saccharomyces cerevisiae Pif1 (ScPif1). Our data showed that when forked dsDNA with free overhangs are used as substrates, both E. coli RecQ and ScPif1 unwind the dsDNA in nonuniform steps that distribute over broad ranges. When tension is exerted on the overhangs, the overall profile of the step-size distribution of ScPif1 is narrowed, whereas that of E. coli RecQ remains unchanged. Moreover, the measured step sizes of the both helicases concentrate on integral multiples of a half base pair. We propose a universal stepping mechanism, in which a helicase breaks one base pair at a time and sequesters the nascent nucleotides and then releases them after a random number of base-pair breaking events. The mechanism can interpret the observed unwinding patterns quantitatively and provides a general view of the helicase activity.

Functional assays for the assessment of the pathogenicity of variants of GOSR2, an ER-to-Golgi SNARE involved in progressive myoclonus epilepsies.

Progressive myoclonus epilepsies (PMEs) are inherited disorders characterized by myoclonus, generalized tonic-clonic seizures, and ataxia. One of the genes that is associated with PME is the ER-to-Golgi Qb-SNARE GOSR2, which forms a SNARE complex with syntaxin-5, Bet1 and Sec22b. Most PME patients are homo-zygous for a p.Gly144Trp mutation and develop similar clinical presentations. Recently, a patient who was compound heterozygous for p.Gly144Trp and a previously unseen p.Lys164del mutation was identified. Because this patient presented with a milder disease phenotype, we hypothesized that the p.Lys164del mutation may be less severe compared to p.Gly144Trp. To characterize the effect of the p.Gly144Trp and p.Lys164del mutations, both of which are present in the SNARE motif of GOSR2, we examined the corresponding mutations in the yeast ortholog Bos1. Yeasts expressing the orthologous mutants in Bos1 showed impaired growth, suggesting a partial loss of function, which was more severe for the Bos1 p.Gly176Trp mutation. Using anisotropy and gel filtration, we report that Bos1 p.Gly176Trp and p.Arg196del are capable of complex formation, but with partly reduced activity. Molecular dynamics (MD) simulations showed that the hydrophobic core, which triggers SNARE complex formation, is compromised due to the glycine-to-tryptophan substitution in both GOSR2 and Bos1. In contrast, the deletion of residue p.Lys164 (or p.Arg196del in Bos1) interferes with the formation of hydrogen bonds between GOSR2 and syntaxin-5. Despite these perturbations, all SNARE complexes stayed intact during longer simulations. Thus, our data suggest that the milder course of disease in compound heterozygous PME is due to less severe impairment of the SNARE function.

Co-expression of lipase isozymes for enhanced expression in Pichia pastoris.

To enhance the overall expression level of lipase isozymes which catalyse the same reaction in Pichia pastoris through co-expression of isozymes from different sources; several types of co-expression ways were constructed to determine the co-expression efficiencies of lipase isozymes in P. pastoris. The results showed that the Kex2-mediated co-expression of lipase isozymes could express Rhizomucor miehei lipase (RML) and Thermomyces lanuginosus lipase (TLL) simultaneously, and GS-RMk-kTL displayed an average lipase activity of 306·91 U ml-1 , higher than GS-RML and GS-kTL (2·89 and 300·59 U ml-1 ) expressed independently in P. pastoris, and the sum of both (303·48 U ml-1 ), implying the potential of isozyme co-expression mediated by Kex2 in increasing the overall recombinant expression, but the low recombinant expression of RML in P. pastoris weakened the overall increasing effect on lipase expression in the isozyme co-expression strains. In addition, the fusion isozymes were successfully expressed, but with low lipase activities. Furthermore, 2A peptide could successfully mediate the co-expression and secretion of lipase isozymes, but it seriously affected the expression of TLL downstream of 2A peptide. SIGNIFICANCE AND IMPACT OF THE STUDY: The low production level is one of the limitation factors for decreasing the prices of enzymes and expanding their application in industry as the biocatalysts. This research focuses on developing lipase isozyme co-expression strategies in Pichia pastoris to enhance the expression level of overall lipase isozymes which catalyse the same reaction. The Kex2-mediated co-expression strategy of lipase isozymes could potentially enhance the overall isozyme expression, and isozyme co-expression might provide a new direction for improving the recombinant isozyme expression, and decreasing the production and application prices of these mixed enzymes as biocatalysts.

Multi-scale encoding of amino acid sequences for predicting protein interactions using gradient boosting decision tree.

Nowadays a number of computational approaches have been developed to effectively and accurately predict protein interactions. However, most of these methods typically perform worse when other biological data sources (e.g., protein structure information, protein domains, or gene neighborhoods information) are not available. In the present work, we propose a method for predicting protein interactions making full use of physicochemical characteristics of amino acids. A protein sequence is encoded at multi-scale by seven properties, including their qualitative and quantitative descriptions, of amino acids. Five kinds of protein descriptors, frequency, composition, transformation, distribution and auto covariance, are extracted from these encodings for representing each protein sequence. The new formed feature representation consisted of 347 dimensions is able to capture not only the compositional and positional information but also their statistical significance of amino acids in the sequence. Based on such a feature representation, the gradient boosting decision tree algorithm is introduced to predict protein interaction class. When the proposed method is tested with the PPI data of S.cerevisiae, it achieves a prediction accuracy of 95.28% at the Matthew's correlation coefficient of 90.68%. Compared with the state-of-the-art works on H.pylori and Human, the accuracies can be raised to 89.27% and 98.00% respectively. Extensive experiments are performed for a crossover protein-protein interactions network and the prediction accuracies are also very promising. Because of learning capabilities of the gradient boosting decision tree and the mutil-scale feature representation scheme, the proposed method might be a useful tool for future proteomics studies.